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Mahrad Sharifvaghefi

Personal Details

First Name:Mahrad
Middle Name:
Last Name:Sharifvaghefi
Suffix:
RePEc Short-ID:psh1197
[This author has chosen not to make the email address public]
https://sites.google.com/view/mahrad

Affiliation

Department of Economics
University of Pittsburgh

Pittsburgh, Pennsylvania (United States)
http://www.econ.pitt.edu/
RePEc:edi:depghus (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Alexander Chudik & M. Hashem Pesaran & Mahrad Sharifvaghefi, 2023. "Variable Selection in High Dimensional Linear Regressions with Parameter Instability," Papers 2312.15494, arXiv.org, revised Jul 2024.
  2. Alexander Chudik & M. Hashem Pesaran & Mahrad Sharifvaghefi, 2020. "Variable Selection and Forecasting in High Dimensional Linear Regressions with Structural Breaks," CESifo Working Paper Series 8475, CESifo.
  3. Marcelo J. Moreira & Mahrad Sharifvaghefi & Geert Ridder, 2017. "Optimal Invariant Tests in an Instrumental Variables Regression With Heteroskedastic and Autocorrelated Errors," Papers 1705.00231, arXiv.org, revised Aug 2021.

Articles

  1. Yingying Fan & Jinchi Lv & Mahrad Sharifvaghefi & Yoshimasa Uematsu, 2020. "IPAD: Stable Interpretable Forecasting with Knockoffs Inference," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(532), pages 1822-1834, December.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Alexander Chudik & M. Hashem Pesaran & Mahrad Sharifvaghefi, 2023. "Variable Selection in High Dimensional Linear Regressions with Parameter Instability," Papers 2312.15494, arXiv.org, revised Jul 2024.

    Cited by:

    1. Christopher F Baum & Andrés Garcia-Suaza & Miguel Henry & Jesús Otero, 2024. "Drivers of COVID-19 in U.S. counties: A wave-level analysis," Boston College Working Papers in Economics 1067, Boston College Department of Economics.

  2. Alexander Chudik & M. Hashem Pesaran & Mahrad Sharifvaghefi, 2020. "Variable Selection and Forecasting in High Dimensional Linear Regressions with Structural Breaks," CESifo Working Paper Series 8475, CESifo.

    Cited by:

    1. Rashad Ahmed & M. Hashem Pesaran, 2020. "Regional Heterogeneity and U.S. Presidential Elections," CESifo Working Paper Series 8615, CESifo.

Articles

  1. Yingying Fan & Jinchi Lv & Mahrad Sharifvaghefi & Yoshimasa Uematsu, 2020. "IPAD: Stable Interpretable Forecasting with Knockoffs Inference," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(532), pages 1822-1834, December.

    Cited by:

    1. Challet, Damien & Bongiorno, Christian & Pelletier, Guillaume, 2021. "Financial factors selection with knockoffs: Fund replication, explanatory and prediction networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 580(C).
    2. Guo, Xu & Li, Runze & Liu, Jingyuan & Zeng, Mudong, 2023. "Statistical inference for linear mediation models with high-dimensional mediators and application to studying stock reaction to COVID-19 pandemic," Journal of Econometrics, Elsevier, vol. 235(1), pages 166-179.
    3. Yoshimasa Uematsu & Takashi Yamagata, 2019. "Estimation of Weak Factor Models," ISER Discussion Paper 1053r, Institute of Social and Economic Research, Osaka University, revised Mar 2020.
    4. Xie, Zilong & Chen, Yunxiao & von Davier, Matthias & Weng, Haolei, 2023. "Variable selection in latent variable models via knockoffs: an application to international large-scale assessment in education," LSE Research Online Documents on Economics 120812, London School of Economics and Political Science, LSE Library.
    5. Pan, Yingli, 2022. "Feature screening and FDR control with knockoff features for ultrahigh-dimensional right-censored data," Computational Statistics & Data Analysis, Elsevier, vol. 173(C).
    6. Liu, Jingyuan & Sun, Ao & Ke, Yuan, 2024. "A generalized knockoff procedure for FDR control in structural change detection," Journal of Econometrics, Elsevier, vol. 239(2).
    7. Zhang, Yaowu & Zhou, Yeqing & Zhu, Liping, 2024. "A post-screening diagnostic study for ultrahigh dimensional data," Journal of Econometrics, Elsevier, vol. 239(2).
    8. Guo, Xu & Li, Runze & Liu, Jingyuan & Zeng, Mudong, 2024. "Reprint: Statistical inference for linear mediation models with high-dimensional mediators and application to studying stock reaction to COVID-19 pandemic," Journal of Econometrics, Elsevier, vol. 239(2).

More information

Research fields, statistics, top rankings, if available.

Statistics

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 3 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-FOR: Forecasting (3) 2020-09-14 2023-02-20 2024-01-15. Author is listed
  2. NEP-ETS: Econometric Time Series (2) 2020-09-14 2023-02-20. Author is listed
  3. NEP-ORE: Operations Research (1) 2020-09-14. Author is listed

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